python: pandas: add values from other dataframe into new column by condition

Question

I have two dataframes with the following data:

fixtures = pd.DataFrame(
    {'HomeTeam': ["A", "B", "C", "D"], 'AwayTeam': ["E", "F", "G", "H"]})

ratings = pd.DataFrame({'team': ["A", "B", "C", "D", "E", "F", "G", "H"], "rating": [
                       "1,5", "0,2", "0,5", "2", "3", "4,8", "0,9", "-0,4"]})

now i want to map the value from ratings["rating"] to the respective team names but i can’t get it to work. is it possible to have new columns with the ratings appear to the right of the HomeTeam and AwayTeam columns?

expected output:

fixtures:

homeTeam  homeTeamRating  awayTeam  AwayTeamRating  
Team A    1,5             Team E    3

Asked By: Robin Reiche

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Source

Answer 1

If you need to apply a method over an existing column in order to compute some values that will eventually be added as a new column in the existing DataFrame, then pandas.DataFrame.apply() method should do the trick.

Answered By: Ritik Pareek

Answer 2

you can use:

to_replace=dict(zip(ratings.team,ratings.rating)) #create a dict. Key is team name value is rating.
#{'A': '1,5', 'B': '0,2', 'C': '0,5', 'D': '2', 'E': '3', 'F': '4,8', 'G': '0,9', 'H': '-0,4'}

fixtures['homeTeamRating']=fixtures['HomeTeam'].map(to_replace) #use map and  replace team column as a new column.
fixtures['AwayTeamRating']=fixtures['AwayTeam'].map(to_replace)

fixtures=fixtures[['HomeTeam','homeTeamRating','AwayTeam','AwayTeamRating']]

'''
  HomeTeam homeTeamRating AwayTeam AwayTeamRating
0        A            1,5        E              3
1        B            0,2        F            4,8
2        C            0,5        G            0,9
3        D              2        H           -0,4
'''

Answered By: Bushmaster

python: pandas: add values from other dataframe into new column by condition

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